More than other factors I am interested in tangible and measurable impact my data science work has on the world. I propose to analyze loan data from Mintos - largest European-based retail lender, but also to dogfood by investing personal funds on the platform, and providing concrete metrics on how my activities contributed to economic well-being of minorities.

The lending structure of Mintos is quite different from two other comparable platforms - Prosper and Lending Club mentioed on TDI blog. Almost all the loans come from 3rd party originators (in 37 countries and 5 continents) that guarantee return of the principal and interest in case of borrower default. In plain terms this means that primary credit risk lies with originators, or originator group, and not with individual borrowers. There has been only 1 originator default in Mintos history, so direct default modelling is not possible. Also, unlike Prosper and Lending Club Mintos has a thriving no fee secondary market, where vintage loans can be bought and sold.

These two structural factors make for a fascinating and complex dataset to analyze, and creating a superior pricing model can provide opportunities for financial gain and improving lives of minorities.